Volume (Incremental) Weighted VOLATILITY BANDS

2019年6月5日

DISCLAIMER:

The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.

The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is following TradingView's regulations. Use of indicator and their code are published by Invitation Only for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).


WARNING NOTICE!

THE INCLUDED FUNCTION MUST BE CONSIDERED AS TESTING. The models included in the indicator have been taken from openly sources on the web, problems could occur at diverse data sceneries.

WHAT'S THIS...?

Work derived by previous own research for study:

The given indicator is another VWAP analysis tool that contains openly procedures for rolling out time sessions as in other TradingView scripts.

Some novelties are introduced in this version:

• INCREMENTAL WEIGHTED STANDARD DEVIATION BANDS: The calculation on this script are strictly based in regard of University of Cambridge Computing Service, February 2009 paper by Tony Finch publicly found at http://people.ds.cam.ac.uk/fanf2/hermes/doc/antiforgery/stats.pdf.
  From the Abstract, he explain how to derive formulae for numerically stable calculation of the mean and standard deviation, which are also suitable for incremental on-line calculation. Then he generalize these formulae to weighted means and standard deviations. He unpick the difficulties that arise when generalizing further to normalized weights. Finally he shown that the exponentially weighted moving average is a special case of the incremental normalized weighted mean formula, and derive a formula for the exponentially weighted moving standard deviation.
  
  
• VOLUME WEIGHTED VOLATILITY ADAPTIVE MOVING AVERAGE & BANDS: Taking the INCREMENTAL WEIGHTED STANDARD DEVIATION already described and taking a specified anchor or Rolling procedure for a VWAP, I derive the variance against the price to use it as VOLATILITY PROXY for a normalization lambda to plot a First Order Impulse Response Filter or Adaptive Average. This idea have it's roots derived from Chaiyuth Padungsaksawasdi & Robert T. Daigler paper entitled "Volume weighted volatility: empirical evidence for a new realised volatility measure".

NOTES:

This version DO NOT INCLUDE ALERTS.
This version DO NOT INCLUDE STRATEGY: Feedback are welcome.


DERIVED WORK:

• Incremental calculation of weighted mean and variance by Tony Finch ([e-mail]) ([e-mail]), 2009.
  
• Volume weighted volatility: empirical evidence for a new realised volatility measure by Chaiyuth Padungsaksawasdi & Robert T. Daigler, 2018.
  
• Multi-Timeframe VWAP by TradingView user @mortdiggidi
  
  
  CHEERS!
  
  xel_arjona 2019.